An empirical study of the effects of knowledge sharing and learning behaviors on firm performance

Knowledge sharing and learning behaviors in the workplace are believed to be very important to the success of firms. In this study, the relationships between knowledge sharing and learning behaviors, business process improvement, product and service offerings, and organizational performance are examined based on a sample of 134 firms engaged in manufacturing, and wholesale or retailing operations. Data analyses using the partial least squares statistical technique revealed that knowledge sharing and learning behaviors are positively associated with business process improvement, and product and service offerings. Business process improvement and product and service offerings are positively associated, and they in turn are positively related to organizational performance. The findings reinforce the importance of knowledge sharing and learning to companies. Executives should encourage knowledge management and organizational learning activities within their firms, and give proper considerations to the strategies and implementation of programs supporting these activities in order to enhance firm performance.     

Artificial intelligence capability: Conceptualization,measurement calibration,and empirical study on its impact on organizational creativity and firm performance

Artificial intelligence (AI) has been heralded by many as the next source of business value. Grounded on the resource-based theory of the firm and on recent work on AI at the organizational context, this study (1) identifies the AI-specific resources that jointly create an AI capability and provides a definition, (2) develops an instrument to capture the AI capability of the firms, and (3) examines the relationship between an AI capability and organizational creativity and performance. Findings empirically support the suggested theoretical framework and corresponding instrument and provide evidence that an AI capability results in increased organizational creativity and performance.     

Data analytics and firm performance: An empirical study in an online B2C platform

Data analytics has become an increasingly eye-catching practice in both the academic and the business communities. The importance of data analytics has also prompted growing literature to focus on the design of data analytics. However, the boundary conditions for data analytics in creating value have been largely overlooked in the literature. The objective of this article therefore is to examine the business value of data analytics usage and explore how such value differs in different market conditions. We rely on an online B2C platform as our empirical setting and obtain several important insights. First, both demand-side and supply-side data analytics usage has a positive effect on the performance of merchants. Second, when merchants’ product variety is high, the influence of usage toward demand-side data on performance is strengthened, whereas such impact is weakened for supply-side data analytics. Third, when competitive intensity is high, the performance implication of demand-side data analytics usage is strengthened, whereas such impact is not strengthened for supply-side data analytics. This study contributes by advancing the overall understanding of business value of data analytics.     

Information technology capability and firm performance: Role of industry

Despite several calls for considering industry in the IS value research, few studies investigated the relationship between benefits of IT and industries. This study extends Chae et al. (2014) by investigating how industry influences the relationship between IT capability and business performance. Unexpectedly, it finds that the control group in the industries in which the "transform" IT strategic role dominates showed superior performance than the IT leader. Also, the IT leaders in the "automate" IT strategic industry did not exhibit better business performance than the control firms. We discuss the implications of these findings.     

An elusive antecedent of superior firm performance: The knowledge management factor

Knowledge management (KM) concepts, principles, and technologies provide a foundation for understanding and building systems for acquiring, assimilating, selecting, generating, and emitting knowledge—a crucial resource of the firm. In the knowledge management community, it is commonly contended that knowledge, and capabilities for processing it, comprise a major resource that can differentiate one firm from another in the sense of yielding better performance or a competitive edge. However, aside from anecdotes, there has been little to substantiate this contention. Can any empirical link be discovered between a firm's KM success and that firm's financial performance? To develop an answer to this question, we use an independent research company's reports of firms judged to be highly successful in their KM initiatives, plus related data reported by COMPUSTAT. As an initial investigation of the linkage between KM performance and firm performance, as measured by financial ratios, this study uses the Matched Sample Comparison Group methodology to evaluate research hypotheses. The analysis reveals a heretofore elusive antecedent of firm performance—evidence that superior KM performance is indeed a predictor of superior bottom-line performance. This study contributes to the information systems (IS) literature by demonstrating that KM, a basic foundation for IS, is an important factor to consider from the standpoint of achieving strong financial performance. As such, it suggests that KM furnishes an important context for understanding designs, applications, and possibilities for IS with respect to achieving such performance. In the context of devising and executing KM initiatives, both technological and human treatments of knowledge need to be cultivated and integrated in ways that lead to superior KM performance. This study also contributes to the management literature by going beyond anecdotes and case studies in buttressing the proposition that a firm's KM competencies are an important ingredient in that firm's performance. It solidifies the raison d'etre for investigating KM phenomena and methods (computer-based and human), both within and across modern organizations. It gives practicing managers evidence that bottom-line benefits are indeed associated with superior KM strategy and execution.     

An empirical investigation of the relationship of IS strategy with firm performance

Given the important impact that an IS strategy has on the potential value IS brings to an organization, we develop and test a model of IS Strategy and Firm Performance. Our survey-based study provides strong evidence that firms with defined IS strategies (either IS Innovator or IS Conservative) perform better than those without defined IS strategies. Organizations without a clearly defined IS strategy actually experienced a negative relationship with firm performance. These organizations should realize the potentially negative outcomes of such a lack of strategy and work to extricate themselves before a consistent pattern of investing in IS without clear organizational benefit develops. Furthermore, the study suggests that the IS Innovator strategy is, in particular, associated with more superior firm performance than the IS Conservative strategy under conditions of environmental dynamism. Organizational leaders need to consider the external environments under which their organizations are operating and evaluate the influence those environments may have on their IS strategy’s ability to impact performance. Post hoc analysis results also reveal a fourth potential IS strategy, one that strives for ambidexterity. Ambidextrous firms were found to be associated with the most superior performance, leading to a potential extension of the existing IS strategy typology and a call for future research.     

Migrant knowledge workers: An empirical study of global Sydney as a knowledge city

Global Sydney is essentially a knowledge city. The global Sydney thesis has focused on Sydney’s performances in the knowledge-based economy, especially the advanced producer services, in an increasingly integrated world economy. Sydney’s emergence as a global city has been inseparable from its migrants from overseas and elsewhere in Australia. This study aims to bridge the theses of global Sydney and migration. The focus is on migrant knowledge workers employed in the knowledge-intensive industries and highly skilled occupations, which are the most reflective of Sydney’s knowledge capacity. Using data from the 2011 Australian Census and a community survey in the Sydney region, this study reveals new insights into the different patterns between international and internal migrant knowledge workers in terms of social–economic backgrounds, drivers for moving to Sydney, and employment before and in Sydney. The findings are useful to better understand migrant knowledge workers in global Sydney, and to contribute to the global city discourse and knowledge city research.     

An empirical study of representing adjectives over knowledge bases: Approach,lexicon and application

Adjectives are common in natural language, and their usage and semantics have been studied broadly. In recent years, with the rapid growth of knowledge bases (KBs), many knowledge-based question answering (KBQA) systems are developed to answer users’ natural language questions over KBs. A fundamental task of such systems is to transform natural language questions into structural queries, e.g., SPARQL queries. Thus, such systems require knowledge about how natural language expressions are represented in KBs, including adjectives. In this paper, we specifically address the problem of representing adjectives over KBs. We propose a novel approach, called Adj2SP, to represent adjectives as SPARQL query patterns. Adj2SP contains a statistic-based approach and a neural network-based approach, both of them can effectively reduce the search space for adjective representations and overcome the lexical gap between input adjectives and their target representations. Two adjective representation datasets are built for evaluation, with adjectives used in QALD and Yahoo! Answers, as well as their representations over DBpedia. Experimental results show that Adj2SP can generate representations of high quality and significantly outperform several alternative approaches in F1-score. Furthermore, we publish Lark, a lexicon for adjective representations over KBs. Current KBQA systems show an improvement of over 24% in F1-score by integrating Adj2SP.     

Determinants of firms' knowledge management system implementation: An empirical study

As knowledge becomes an increasingly valuable and important organizational asset, many firms anticipate that implementing the knowledge management systems (KMS) will effectively support and enhance organizational knowledge management activities. Even some firms regard KMS as an emerging and powerful source of competitive advantages.However, the implementation of KMS differs from that of traditional enterprise information systems. The implementation of KMS is difficult and risky since these systems are unstructured and so technologically innovative. Thus, effort is required to identify determinants affecting KMS implementation in businesses.Based on innovation diffusion theory and technology-organization-environment framework, this study develops and tests an integrated model of knowledge management systems implementation for businesses. Survey data were collected from 291 businesses in Taiwan. Confirmatory factor analysis and logistic regression technique were used test the hypothesized relationships. The results show that technological innovation factors (perceived benefits, complexity, and compatibility), organizational factors (top management support, organizational culture), and environmental factors (competitive pressure) are significant influences on KMS implementation in firms. Finally, the implications and future research on KMS implementation are discussed.     

Estimating the impact of cloud computing on firm performance: An empirical investigation of listed firms

This study empirically investigates the economic impact of cloud service adoption on firm performance. We exploit the difference-in-differences models coupled with propensity score-based matching to estimate the performance effect of cloud computing on worldwide listed firms that adopted cloud service during 2010–2016. The results indicate that cloud computing has a significant and positive impact on the profitability and market value of listed firms with varying degrees in both short and long time periods. In addition, the magnitude of the performance effect varies with firm size and industry type. This research contributes to empirical examination on the economic values of IT investments.     

Acquiring and sharing tacit knowledge in software development teams: An empirical study

ContextSharing expert knowledge is a key process in developing software products. Since expert knowledge is mostly tacit, the acquisition and sharing of tacit knowledge along with the development of a transactive memory system (TMS) are significant factors in effective software teams.ObjectiveWe seek to enhance our understanding human factors in the software development process and provide support for the agile approach, particularly in its advocacy of social interaction, by answering two questions: How do software development teams acquire and share tacit knowledge? What roles do tacit knowledge and transactive memory play in successful team performance?MethodA theoretical model describing the process for acquiring and sharing tacit knowledge and development of a TMS through social interaction is presented and a second predictive model addresses the two research questions above. The elements of the predictive model and other demographic variables were incorporated into a larger online survey for software development teams, completed by 46 software SMEs, consisting of 181 individual team members.ResultsOur results show that team tacit knowledge is acquired and shared directly through good quality social interactions and through the development of a TMS with quality of social interaction playing a greater role than transactive memory. Both TMS and team tacit knowledge predict effectiveness but not efficiency in software teams.ConclusionIt is concluded that TMS and team tacit knowledge can differentiate between low- and high-performing teams in terms of effectiveness, where more effective teams have a competitive advantage in developing new products and bringing them to market. As face-to-face social interaction is key, collocated, functionally rich, domain expert teams are advocated rather than distributed teams, though arguably the team manager may be in a separate geographic location provided that there is frequent communication and effective use of issue tracking tools as in agile teams.     

An empirical study of testing and integration strategies usingartificial software systems

There has been much discussion about the merits of various testing and integration strategies. Top-down, bottom-up, big-bang, and sandwich integration strategies are advocated by various authors. Also, some authors insist that modules be unit tested, while others believe that unit testing diverts resources from more effective verification processes. This article addresses the ability of the aforementioned integration strategies to detect defects, and produce reliable systems. It also explores the efficacy of spot unit testing, and compares phased and incremental versions of top-down and bottom-up integration strategies. Relatively large artificial software systems were constructed using a code generator with ten basic module templates. These systems were seeded with known defects and tested using the above testing and integration strategies. A number of experiments were then conducted using a simulator whose validity was established by comparing results against these artificial systems. The defect detection ability and resulting system reliability were measured for each strategy. Results indicated that top-down integration strategies are generally most effective in terms of defect correction. Top-down and big-bang strategies produced the most reliable systems. Results favored neither those strategies that incorporate spot unit testing nor those that do not; also, results favored neither phased nor incremental strategies     

独立董事特征与公司绩效关系的实证研究

在梳理国内外大量文献的基础上,对独立董事特征与公司绩效的关系进行分析并提出了研究假设。以深圳证券市场中小板上市公司为研究样本,用SPSS13.0软件对我国中小型上市公司独立董事特征与公司绩效进行了典型相关分析,结果显示,独立董事与公司绩效之间存在不显著的相关关系。     

Impact of absorptive capability on software process improvement and firm performance

Software process improvement (SPI) is a continual organizational learning process with the goal of obtaining and sustaining competitive advantage in rapidly developing business and software environments. However, no research has focused on a firm’s capability to increase effective external SPI knowledge acquisition and utilization. Thus, this study uses dynamic capability theory in order to investigate empirically the capability of a firm to absorb external knowledge and achieve SPI. Specifically, we propose a research model and examine the relationships among a firm’s potential absorptive capability (PAC), realized absorptive capability (RAC), SPI success, and firm performance. In this regard, we surveyed 108 respondents in 56 SPI-certificated Taiwanese firms. We then tested our model using a partial least squares structural equation modeling technique. The results indicate that SPI success is significantly influenced by PAC through RAC. The results also suggest that absorptive capability is critical to SPI success and that the latter ultimately influences firm performance.     

An empirical study of domain knowledge and its benefits tosubstructure discovery

Discovering repetitive, interesting, and functional substructures in a structural database improves the ability to interpret and compress the data. However, scientists working with a database in their area of expertise often search for predetermined types of structures or for structures exhibiting characteristics specific to the domain. The paper presents a method for guiding the discovery process with domain specific knowledge. The SUBDUE discovery system is used to evaluate the benefits of using domain knowledge to guide the discovery process. Domain knowledge is incorporated into SUBDUE following a single general methodology to guide the discovery process. Results show that domain specific knowledge improves the search for substructures that are useful to the domain and leads to greater compression of the data. To illustrate these benefits, examples and experiments from the computer programming, computer aided design circuit, and artificially generated domains are presented     

Data quality and firm performance: empirical evidence from the Korean financial industry

Despite popular belief that timely and precise data are important and indispensable to good decisions and that good decisions are related to better firm performance, empirical research that examines the effect of data quality on firm performance is still scarce. How great an impact does data quality have on firm performance? This study empirically investigates the effect of firm-level data quality on firm performance in the Korean financial industry during 2008–2010. The results show that commercial banks have high-quality data, while credit unions have comparatively low-quality data. They also show that better data quality has a positive influence on sales, operating profit, and value added. Improving the level of data quality management maturity by one can increase firm performance by 33.7 % in sales, 64.4 % in operating profit, and 26.2 % in value added.     

An empirical study on m-learning adaptation: Learning performance and learning contexts

M-learning enables students to learn everywhere and at any time. But mobility also brings a new challenge. Students may now be constantly moving and the context from which they learn has to be adjusted dynamically. Therefore adaptation is becoming increasingly important when it comes to m-learning. This paper presents an empirical study to assess the learning performance and attitude of graduate students when they use an adaptive mobile system that tailors learning contents to their skills, their device and current context. Results suggest that mobile adaptation had a limited impact in learning performance of practical skills when compared to an e-learning approach. Information about the context of use of the mobile system was also collected and compared with traditional computer accesses. Results suggest that students learned in similar context independently of the way that they used to access learning contents. This may challenge current assumptions about the mobility of students.     

An empirical evaluation of knowledge,cognitive style,and structure upon the performance of a hypertext task

In an effort to reduce navigation difficulties, recent research suggests that user characteristics need to be considered when designing a hypertext document. This study evaluated the effects of an individual's cognitive characteristics in conjunction with the nature of the hypertext task. Subjects of varying levels of knowledge and cognitive style, specifically field independence/field dependence, utilized a hypertext document to answer explicitly and inherently structured questions. Among other findings, experienced field‐dependent subjects’ performance was less than that of experienced field‐independent subjects’, specifically when explicit structure was provided. The results suggest that the existing knowledge structure of experienced field‐dependent subjects may conflict with explicitly structured hypertext. Implications for the appropriate design of hypertext systems are discussed.     

Information technology,the organizational capability of proactive corporate environmental strategy and firm performance: a resource-based analysis

The study of the relationships between information technology (IT), environmental organizational issues and firm performance is a cutting-edge research topic for the information systems (IS) community. However, at present we know very little about these relationships. Drawing on the perspective of IT-enabled organizational capabilities and the literature on organizations and the natural environment, our study introduces conceptually the construct organizational capability of proactive corporate environmental strategy to the IS field. We propose that IT capability may enable the implementation of a proactive environmental strategy and that this strategy could play a significant role in determining the business value of IT. Using structural equations modeling with data collected from 63 firms, we find that IT capability is an enabler of proactive environmental strategy and that this strategy plays a significant role in mediating the effects of IT on firm performance. Our study provides initial evidence on the role of IT in the implementation of proactive environmental practices. Our results suggest to IT executives that their decisions matter in shaping environmental sustainability, which in turn will generate business value from IT.